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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 9,199 Documents
 87   88   89   90   91 
Detecting Community and Topic Co-Evolution in Social Networks Juan Bi; Zhiguang Qin; Jia Huang
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 5: May 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

In this paper we study how to discover the co-evolution of topics and communities over time in dynamic social networks. We present a topic model-based approach that automatically captures the dynamic features of communities and topics evolution. Our model can be viewed as an extension of the LDA model with the key addition that it can not only detect communities and topics simultaneously but also work in an online fashion. Instead of modeling communities and topics in statistical manner, the proposed model can simulate the user’s interests drifting at different time epochs by taking into consideration the temporal information implied in the data, and observe how the community structure changes over time with the evolution of topics. Experiments on real-world data set have proved the ability of this model in discovering well-connected and topically meaningful communities and the co-evolution pattern of topics and communities. DOI : http://dx.doi.org/10.11591/telkomnika.v12i5.4389 
An IOT Security Risk Autonomic Assessment Algorithm Ruijuan Zheng; Mingchuan Zhang; Qingtao Wu; Chunlei Yang; Wangyang Wei; Dan Zhang; Zhengchao Ma
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: February 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

In terms of Internet of Things (IOT) system with the possibility criterion of fuzziness and randomness security risk, we qualitatively analyze the security risk level of IOT security scene by describing generalization metrics the potential impact and likelihood of occurrence of every major threat scenarios. On this basis, we proposed self-assessment algorithm of IOT security risk, adopting three-dimensional normal cloud model integrated consideration of risk indicators, researching the multi-rule mapping relationship between the qualitative input of safety indicators and the quantitative reasoning of self-assessment. Finally, we build security risk assessment simulation platform, and verify the validity and accuracy of the algorithm in the premise of substantiating the risk level and the safety criterion domain. DOI: http://dx.doi.org/10.11591/telkomnika.v11i2.2030
Assault Discovery and Localizing Adversary in Remote Networks Patel KalpanaDhanji; Santhoshkumarsingh Santhoshkumarsingh
Indonesian Journal of Electrical Engineering and Computer Science Vol 9, No 1: January 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v9.i1.pp81-84

Abstract

Remote Systems are presently prevalent worldwide to help individuals and machines to speak with each other regardless of their area, where it has an unending mission for expanded limit and enhanced quality. Despite the fact that there are many points of interest yet regardless it have a few burdens. This paper manages the vulnerabilities in the remote frameworks. The vulnerabilities show in the remote innovation that is generally identified with dangers and dangers. Despite the fact that much defencelessness are in the remote frameworks this paper for the most part manages the parodying assaults. In remote frameworks the foes can dispatch any kind of assaults to take the information and to lull the execution of the system. The fundamental driver of this paper is to pass on that remote frameworks require a more grounded instrument. So we likewise propose to perform equipment execution utilizing a Zig honey bee handset which utilizes the standard (802.15.4) chiefly in view of Zigbee convention Stack.
Detection of keratoconus in anterior segment photographed images using corneal curvature features Marizuana Mat Daud; Wan Mimi Diyana Wan Zaki; Aini Hussain; Haliza Abdul Mutalib
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 3: March 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i3.pp1191-1198

Abstract

Keratoconus is a corneal ectatic disorder with complex aetiology and may induce mild to severe visual impairment and consequently decrease the quality of life. This paper presents a new keratoconus detection method using corneal curvature features to differentiate normal and keratoconus cases. In this study, the eye images known as anterior segmented photographed images (ASPIs) are captured from side view using a smartphone’s camera. For the side-view images, the corneal curvature is segmented using spline function to measure the corneal curvature. A template disc method is implemented to quantitatively measure the steepening of the corneal curvature of the captured ASPIs. Parameters obtained from three different template disc methods, namely, nonlinear, , crossover point, , and trigonometric, , are investigated to represent the most suitable curvature feature. SVM is then employed to classify normal and keratoconus eyes. Results reveal that a standalone nonlinear method gives a reliable parameter with 90% accuracy in classifying the data. However, the classification performance has increased to 99.5% accuracy with the use of all combined features known as a feature vector, . Additionally, classification with the proposed  has successfully distinguished normal and keratoconus cases with sensitivity and specificity rates of 99% and 100%, respectively. The results portray the bright potential of this method in assisting experts during ocular screening specifically to detect keratoconus disease.
A Bisection Method for Information System Knowledge Reduction Zhi Huilai
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 9: September 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

In rough set theory, attribute reduction aims to retain the discernability of the original attribute set, and many attribute reduction algorithms have been proposed in literatures. However, these methods are computationally time-consuming for large scale datasets. We develop a bisection method for attribute reduction and the main opinion is to partition the universe into smaller ones by using partition core attributes to reduce the complexity. Experiments and analysis show that, compared with the traditional un-bisection reduction algorithm, the developed bisection algorithm can significantly reduce computational time while maintaining their results as same as before. http://dx.doi.org/10.11591/telkomnika.v12i9.4913 
Soft-Sensing Modeling Method of Vinyl Acetate Polymerization Rate Jiangping Huang; Wenzhi Luo; Anan Liu
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 6: June 2013
Publisher : Institute of Advanced Engineering and Science

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Abstract

In the procedure of polyvinyl alcohol production, it is hardly accurate measuring the Vinyl Acetate (VAC) polymerization rate. To solve this awkward situation, this paper adopt Genetic Algorithm-Back Propagation (GA-BP) Neural Network to fit the nonlinear relation of the variables which derives from the production process by setting the VAC polymerization rate as the master variable and the initiator addition ratio, methanol ratio, polymerization temperature and VAC activity degree as auxiliary variables. Establish VAC polymerization rate soft-sensing model based on GA-BP network which the connection weights optimized by genetic algorithm. The comparison results with BP network based on the actual measured data show that the model this paper constructed is accurate and effective. DOI: http://dx.doi.org/10.11591/telkomnika.v11i6.2724
Logic mining in football matches Liew Ching Kho; Mohd Shareduwan Mohd Kasihmuddin; Mohd. Asyraf Mansor; Saratha Sathasivam
Indonesian Journal of Electrical Engineering and Computer Science Vol 17, No 2: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v17.i2.pp1074-1083

Abstract

Sports results forecast has became increasingly popular among the fans nowadays. It made predicting the outcome of a sport’s match, a new and interesting challenge. This paper presented a logic mining technique to model the results (Win Draw / Lose) of the football matches played in English Premier League, Spanish La Liga and France Ligue 1. In this research, a method namely k satisfiability based reverse analysis method (kSATRA) hybridized with Ant Colony Optimization (ACO) was brought forward to obtain the logical relationship among the clubs in these leagues. The logical rule obtained from the football matches was used to categorize the results of future matches. ACO is a population-based and nature-inspired algorithm to decipher several combinatorial optimization problems. kSATRA made use of the advantages of Hopfield Neural Network and k Satisfiability representation. The data set used in this study included the data of 6 clubs from each league, which composed of all league matches from year 2014 to 2018. The effectiveness of kSATRA with ACO in obtaining logical rule in football matches was tested based on root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE) and CPU time. Results acquired from the computer simulation showed the robustness of kSATRA in exhibiting the performance of the clubs.
Design of a Subsequent Water Detection System Controlled by the Microcontroller Chu Yan; Tang Kang; Feng Xiaoming; Cai Xinyuan; Chen Pengju
Indonesian Journal of Electrical Engineering and Computer Science Vol 12, No 1: January 2014
Publisher : Institute of Advanced Engineering and Science

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Abstract

This article instructs the subsequent water detection system design and implementation of sanitary ware. This system used C8051f040 Microcontroller as the main control module and communication module which controlled the operation of the entire system，touch screen as a position machine，and made use of metal probing technique and weighing sensor technology to realize data test、collection、display、storage and export. At last，the experimental results showed that this system meet the expected requirement and can measure the subsequent water more accurately. DOI : http://dx.doi.org/10.11591/telkomnika.v12i1.4140 
Designing of Medical processor unit for Intelligent network-based Medical usage P. ILA Chandana Kumari; P. Gayathri; N. Rajesh; Syed Umar; G. Chandra Sekhar; Azeem Mohammed Abdul
Indonesian Journal of Electrical Engineering and Computer Science Vol 4, No 3: December 2016
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v4.i3.pp532-537

Abstract

This medical design conventions of books and deductive method (MPU). the development of research and the success of many already, we have found the cause of architecture MPU. On the unique features of the processor in question it is coded in different areas of medicine (MOPC). working from a very close bilateral processor MPU. Each issue has a special feature code for the hardware supply chain on the steps and produce a special version of the code and the victim (s). Illness, Doctor MOPC mph dismounted and made a series of sub-processes, and to launch the second law of medical devices. If the computer system of a victim and has a specific digital for logic, and victims of medical devices that operate in the blood, tissues, operating theaters, medical staff, medical costs and variables, etc. We follow the process that the patient design of medical networks and overlapping and development computer.
A Tiered Approach On Dimensional Reduction Process for Prediction of Coronary Heart Disease Wiharto Wiharto; Herianto Herianto; Hari Kusnanto
Indonesian Journal of Electrical Engineering and Computer Science Vol 11, No 2: August 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v11.i2.pp487-495

Abstract

The use of dimensional reduction in the diagnostic system model of coronary heart disease, many same of case do not take into account the clinical procedures commonly used by clinicians in diagnosis. This requires that the examination be done thoroughly, thus making the high cost of diagnosis. This study aims to develop a tiered approach model in reducing dimensions for predicting CHD. The method in this research is divided into several stages, namely preprocessing, building the knowledge base and system testing. Preprocessing consists of several processes, namely the removal of missing value data, grouping attributes, and dividing data for training and testing. Knowledge base modeling is divided into three levels. The first level were the risk factor attributes, the second level were the type of chest pain & ECG, and the third were scintigraphy & coronary angiography. The knowledge base was modeled based on fuzzy rules and its inferencing process using Mamdani method. The first, fuzzy rule-based was obtained by using the FRS study. The second and third stage, using the induction rule algorithm to get the rule, then converted to fuzzy rule. The tested algorithm were C4.5, CART, and FDT. The system testing was performed by the 5-folds cross-validation method, with performance parameters based on population and individual. The test resulted using the Cleveland and Hungarian datasets, the FRS+CART combination was capable of reducing the most attributes and the highest likelihood ratio performance parameter, which was 15.96. FRS+C4.5, at least the attributes were reduced, but has an AUC performance of 80.43%, while FRS+FDT, more reduced attributes than FRS+C4.5, and AUC performance parameters are better than FRS+CART. Dimensional reduction model for prediction of CHD, capable of providing better performance than not tiered.

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